Why You’re Not Solving the Problem You Think You’re Solving with AI

Why You’re Not Solving the Problem You Think You’re Solving with AI

Join Seth Juarez as he delves into ethical concerns with AI with Josh Lovejoy, who leads Design for Microsoft Ethics & Society within Cloud + AI, and Sarah Bird, who leads Responsible AI for Cognitive Services.

This video explores how to think about Ethical AI and how to ensure the software you build is designed, developed and deployed ethically. Josh and Sarah describe how Ethics & Society works closely with product teams to make human-centered AI / ML technologies that serve people by appreciating the constraints and measuring accuracy and inaccuracy throughout the product development lifecycle.

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OSS Framework Support in Azure Machine Learning Service

OSS Framework Support in Azure Machine Learning Service

Learn how Azure ML supports Open Source ML Frameworks and MLflow in AzureML.

Take a walk through a ScikitLearn and Pytorch example to show the built in support for ML frameworks.

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PowerPoint Designer: Powered by Azure Machine Learning Service

PowerPoint Designer: Powered by Azure Machine Learning Service

Powerpoint Designer utilizes machine learning to provide users with redesigned slides to maximize their engagement and visual appeal.

Up to 4.1 million Designer slides are created daily and the Designer team is adding new types of content continuously.

Time Index:

  • [02:39] Demo – PowerPoint suggests design ideas to help users build memorable slides effortlessly
  • [03:28] A behind-the-scenes look at how PowerPoint was built to make intelligent design recommendations
  • [04:47] AI focused on intelligently cropping images in photos and centering the objects, positioning the images, and even using multi-label classifiers to determine the best treatment.
  • [06:00] How PowerPoint is solving for Natural Language Processing (NLP).
  • [07:32] Providing recommendations when image choices don’t meet the users’ needs.
  • [09:30] How Azure Machine Learning helps the dev team scale and increase throughput for data scientists.
  • [11:10] How distributed GPUs helps the team work more quickly and run multiple models at once.